Ontology Based Sports Video Annotation and Summary

With digital sports video increasing everyday, effective analyzing sports video content becomes more and more important. Effective and efficient representation of video for searching, retrieval, inference and mining is a key problem in knowledge engineering. To describe sports video content efficiently, sports video ontology for video annotation is represented in OWL, a description logic based Web Ontology Language. We describe a user-friendly platform for sports video annotation. Ontology based sports video annotation can facilitate video indexing, retrieval and reasoning in a broad range of applications including Digital Olympic Project in China. Moreover, we present a hierarchical sports video summarization strategy to browse the sports video in a progressive way. In sports video, replay scenes often represent the highlight or interesting event of the video. Hence, our representative scene selection is based on the replay detection algorithm and identical events detection. The basic experimental results show our strategy is effective.